Blog
AI in Insurance: A Powerful Potential for Growth
Where Insurers Are Focused
Many insurance companies have already started their technology transformation journeys, with 60% of insurers identifying AI as a digital transformation initiative being pursued. GenAI, however, is still in its infancy for many organizations. 41% of companies indicate that they don’t yet have plans for its deployment; it’s clear there’s both an opportunity and a challenge for insurers to innovate and scale AI beyond natural language processing (NLP) and machine learning (ML).
And yet, the companies that are leading the way—particularly those with over $1 billion in revenue—are proving to be trailblazers in adopting AI in insurance. These organizations are leveraging AI-driven insights to improve customer experiences with tools like feedback analysis, chatbots, and personalized interactions. They’re borrowing techniques from industries like ecommerce and entertainment, reshaping customer expectations in the insurance space. And using agentic AI solutions like Concentrix’s own iX Hello™.
The common thread in this story of transformation—organizations are deploying AI to meet their main objective of better understanding and serving customers.
Are Insurers Measuring Success Effectively?
For all the promise and excitement surrounding AI, there’s one critical question we can’t overlook—are we measuring its success effectively?
Almost half of insurance companies report they only measure some of their GenAI outcomes, while just 14% say they track everything comprehensively. That lack of visibility creates a bottleneck for progress, leaving organizations unable to assess the impact of their AI initiatives and, more importantly, decide on next steps to improve.
This gap in measurement is leading to two distinct challenges:
- Companies implement AI without measuring its true value.
- Companies measure AI outcomes but fail to meet expectations due to inadequate execution or unaddressed challenges.
At its core, this means there’s a massive untapped potential for AI to drive transformation across the insurance sector. But first, you’ll need to navigate the roadblocks.
The Roadblocks to AI in Insurance
The number one barrier for insurers trying to scale AI adoption is the lack of skilled personnel.1 44% of all respondents identified this as their major challenge to leveraging GenAI. This issue isn’t just about recruiting engineers or training frontline teams. It’s about having capable talent in every department—from strategy to operations—who thoroughly recognize the nuances of AI and its potential applications.
Partnerships can also be a sticking point, since consumption-based commercial models can use financially driven motivations to choose one platform or capability over the other. That’s why it’s important to choose a partner who can help cut costs for insurance companies while also enhancing operations across the entire enterprise.
Insurers face more challenges including data privacy concerns and regulatory issues, as well as oversaturated IT infrastructures. These obstacles collectively limit the industry’s ability to fully see the benefits of AI for innovation and enhanced customer experiences.
Additionally, industry decision-makers may struggle with achieving alignment across teams when deliberating which AI platform to leverage in their organization. This makes it especially crucial for such platforms to provide end-to-end capabilities, covering a wide range of organizational and customer-focused needs.
Succeeding with AI: Strategies for Insurance Companies
For successful AI implementation, insurance companies require a clear strategy that includes:
- Evaluating Needs and Partnerships: On a basic level, insurers must identify specific business needs AI can address. Then, choose partners who align with the unique needs of your business, develop a deep and positive rapport with your teams, and can move your AI initiatives to the next phase and beyond. Collaborating with experienced partners can facilitate this transition effectively.
- Ensuring Data Quality and Privacy: With data being the backbone of AI, maintaining its quality and security is paramount. Insurance firms must implement robust data governance frameworks to safeguard customer information and comply with regulations.
- Fostering a Customer-Centric Approach: Personalizing customer interactions and addressing unique needs can differentiate an insurance company in a crowded market. AI provides the tools to anticipate customer requirements and make interactions memorable.
The Competitive Advantage Awaits
The future of AI in insurance may start with operational efficiency, but there are more use cases still being discovered. For instance, AI-powered systems can detect errors, organize data, and swiftly process large volumes of information.² Its ability to analyze large data sets and predict customer behaviors will become indispensable. Insurance companies that strategically adopt AI stand to enhance both their bottom line and their customer relationships, setting new standards in the industry.
While there’s no doubt that implementing AI can be challenging, the rewards exceed the risks. By addressing technology gaps, measuring outcomes holistically, and partnering with the right experts, insurers can achieve truly transformational success.
If you’re in the insurance industry and want to lead the way in AI adoption, focus on bridging the gap between technology and human insights. The benefits will be evident through higher operational efficiency, and they will also empower your teams to deliver better, more personalized experiences to your customers by building trust, loyalty, and long-term success along the way.
Ready to take the next leap? Read our full report to learn more about how AI can transform your business strategy.
Dan Holbrook
Director, CX Consulting, Insurance
